This Week’s Updates

Enabling the Team

Finally, The Handoff Is Dead by Luke Wroblewski
AI does not fix collaboration on its own. Teams work better when design decisions, development standards, and project context are carried in a shared system so people can contribute in parallel without losing alignment or creating handoff waste.

AI Layoffs: The Leadership Choice Behind Every Headline by Pim de Morree
AI layoffs dominate headlines, but IKEA proves there's another way. When AI could replace 57% of their work, they chose reskilling over firing.

Product Direction

Outcomes Vs. Outputs: What's The Difference And Why Does It Matter? by Teresa Torres
Product teams make better decisions when they measure the impact of what they ship, not just whether it shipped. Choosing outcomes that reflect real customer value helps teams avoid feature-factory thinking, focus discovery on the right problems, and stay accountable for results instead of delivery alone.

The AI Documentation Paradox by Florian Bonnet
AI makes it easier to produce polished documentation, but that does not mean teams are thinking more clearly or making better decisions. Shorter, sharper docs that lead with the decision and separate judgment from evidence are more useful than longer documents that signal effort without changing the quality of the thinking.

Continuous Research

The missing Seat At The Frontier Team Table by Martin Linde Danty, Rabeeza A., Anne Klærke-Olesen, Madhumay Sinha, and Michael O’Sullivan
AI evaluations work better when researchers help define what “good” looks like before teams start measuring it. Bringing qualitative insight into scenarios, assumptions, and success criteria helps teams catch unrealistic abstractions, avoid misleading metrics, and build AI features that perform well in real workflows instead of just looking good in evals.

The Research Operating System Too Few Are Building: Why “I-Me-Mine AI” Isn't Enough by Kate Towsey
Research teams will get more value from AI when they stop treating it as an individual productivity tool and start building shared systems around where it should be used, where it should not, and what good looks like. Clear standards, guardrails, and workflows help research scale more safely and make it easier for the function to create visible organizational value instead of isolated efficiency gains.

Continuous Design

What Designers Actually Struggle With On Product Teams by Laura Klein
Designers create more impact when they are brought in early, can connect user needs to business outcomes, and have clearer ways to work with product, engineering, and stakeholders. Alignment, influence, and role clarity matter as much as craft when teams are trying to shape better product decisions.

Google Says “Vibe Design” Is Here, But It Didn’t Pass My Vibe Check by Elvis Hsiao
AI can take on more of the making, but designers still create value through problem framing, taste, judgment, and deciding what is worth building in the first place. The pressure is real, but the stronger response is to use AI to extend your range while protecting the thinking skills that generic outputs still cannot replace.

Continuous Development

The Golden Rules Of Agent-first Product Engineering by Jina Yoon
Agent-first products work better when teams give agents full product capabilities, expose the right abstraction layer, front-load the context every session needs, and encode product judgment into the system. Treating agents like real users through dogfooding, trace review, and evals helps teams catch fragile experiences earlier and improve trust before bad behavior scales.

Explaining, Understanding, And Data Compression by Anton Zaides
Technical leaders are more effective when they explain complex thinking in a way others can actually absorb. Clearer communication, fewer unnecessary details, and checking what people understood can reduce confusion, speed up alignment, and make feedback more useful.

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Managing Your Career In The Age Of AI

Have You Read My E-Book Yet?

AI is changing the shape of product, UX, design and engineering careers. Junior-level tasks are being automated, expectations are shifting, and the skills that help people progress are becoming less about output and more about judgment, influence and cross-functional thinking. My ebook, Managing your Career in the Age of AI, breaks down the 4 levels of career thinking, the shift from pyramid to diamond-shaped teams, and why the old T-shaped skills model is giving way to a more connected, comb-shaped approach.

Download the ebook to understand where you are today, what skills matter next, and how to position yourself for the AI-powered world of work.

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Video Of The Week

From Cross-Functional To Cross-Purposes:
Why Collaboration Falls Apart Over Time

Cross-functional teams do not fall out of alignment because people stop caring about collaboration. More often, the problem is hidden in the structures, habits, and language teams use every day.

In this talk, Mihaela Draghici shares what she learned from embedding business stakeholders into hybrid product teams and why even strong collaboration frameworks can slowly break down. A practical watch for anyone trying to keep product, business, and engineering aligned beyond the first workshop, kickoff, or team restructure:

Want to go into how careers and leadership are shifting as AI compresses the ladder? My ebook Managing Your Career In The Age Of AI explores how to build judgment, relationships, and influence in a world that keeps trying to automate the surface of the work.